Optimal Stochastic Prediction and Verification of Signal-to-Noise Ratio and Data Rate for Ka-Band Spaceborne Telemetry Using Weather Forecasts

An improved weather-forecast-based link-budget design technique for space-to-Earth links is described. The aim is the stochastic optimization of both transmission symbol rate and received signal-to-noise ratio. The proposed radiometeorological operations prediction (RadioMetOP) model takes into account the forecast uncertainty by a space–time ensemble method exploiting the temporal evolution of the predicted radiometeorological variables over the weather-forecast spatial grid. The unique possibility of testing and validating the RadioMetOP model is presented, thanks to the $Ka$ -band downlink measurements available from the support of the European Space Agency’s antenna tracking network to deep-space Hayabusa-2 (HB2) mission, operated by the Japan Aerospace Exploration Agency. First, the RadioMetOP model accuracy is tested by comparing the signal-to-noise ratio, measured during the transmission periods, with the simulated one, properly scaled to the symbol rate operated by HB2, finding correlation values of 0.9 that confirm the effectiveness of the proposed approach. Second, the $a$ posteriori analysis of the optimization process is accomplished, showing that depending on the considered criteria for the link-budget optimization, the use of the RadioMetOP model would have allowed a transmitted data volume more than doubled and an average signal-to-noise ratio gain between 2.1 and 3.8 dB.